{"id":"W4298033315","doi":"","title":"An illustrated glossary of ambiguous PLM terms used in discrete manufacturing","year":2015,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Glossary; Manufacturing engineering; Engineering; Computer science; Linguistics; Philosophy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00113747,0.0001519464,0.0001867569,0.000138597,0.00005019811,0.00008934362,0.000379452,0.00009585876,0.00003634079],"category_scores_gemma":[0.00009661951,0.0001571576,0.00003745117,0.0001954163,0.00006367973,0.0002859911,0.00006076331,0.0001623024,0.000005993977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006196793,"about_ca_system_score_gemma":0.00003429099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007755051,"about_ca_topic_score_gemma":0.0008061251,"domain_scores_codex":[0.9985933,0.0004546237,0.0003146676,0.0002230073,0.000202475,0.0002119537],"domain_scores_gemma":[0.9988731,0.00008004512,0.00009156911,0.0006069064,0.00021599,0.0001324087],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000974936,0.001132646,0.02995856,0.001038192,0.0001458831,0.00003897497,0.0493785,0.7443398,0.02382128,0.01005199,0.0004516946,0.1395449],"study_design_scores_gemma":[0.0009917299,0.000001121095,0.02441418,0.0004387476,0.00001264013,0.00000534763,0.0002588184,0.2995979,0.6723524,0.0008300125,0.0007419971,0.0003550738],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.91843,0.0001173901,0.06743358,0.0002148978,0.00007644343,0.0001499417,0.000012384,0.0002401623,0.01332516],"genre_scores_gemma":[0.9906062,0.00005195651,0.008714461,0.000008867676,0.000007677725,0.00001154055,0.0001208523,0.0000303633,0.0004480603],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6485311,"threshold_uncertainty_score":0.64087,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.013006791479581,"score_gpt":0.2125055171050386,"score_spread":0.1994987256254576,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}